Analysis of Sustainability Specifications of Urban Air Mobility Fleet Operations using Agent-based Transportation Simulation

Abstract

Due to increasing requirements for energy efficiency, noise, and costs of transportation modes from both user and legal perspectives, Urban Air Mobility (UAM) concepts need to be evaluated in the context of sustainability. This is further motivated by continuously evolving electric vehicles with vertical take-off and landing (eVTOL) capabilities for urban application scenarios and consequently there is a need for analysis on the overall system level. This paper aims at investigating environmental friendliness, noise, and costs impacts on the feasibility of UAM by using agent-based transportation simulation and cost modeling. Latest fleet optimization approaches are extended for sustainability specifications while optimized costs and simulated demand behavior for given UAM ticket prices are looped in an iterative modeling. The studies are conducted in the simulation scenario Ruhr (West Germany) of the Multi-Agent Transport Simulation (MATSim). Results show that the use of UAM flights substitutes a relevant share of ground-based transportation, corresponding to over 30 % reduction in carbon dioxide equivalents of the eVTOL vehicle compared to its status quo. With regard to total costs, a pricing of carbon dioxide equivalent emissions from 200 €/t can be determined as an upper bound for feasibility in the case study. There, a total price of 1.26 € per passenger-kilometer is found to be targeted as higher prices reduce UAM demand and lower prices increase system costs and complexity disproportionately. Furthermore, despite lower user acceptance, autonomous modes of transportation are decisive for future feasibility in the considered scenario, as are maximum noise emissions of 75 dB at a distance of 100 m to hovering eVTOL vehicles. Finally, the applied methodology allows for further case studies and enables the assessment of both UAM network scenarios and eVTOL vehicle performance on fleet level.